PROJECT SUMMARY Climate change is increasingly recognized as the biggest public health threat of the 21st century. A projected acceleration of global warming in coming decades is expected to increase the frequency and severity of future natural disasters, including severe coastal storms and floods. A growing body of literature documents the health impacts associated with these events, which can occur through multiple pathways, including direct exposure to the storm and storm-related damage (e.g., falling trees or building debris), disorganized or unheeded evacuations, post-storm infrastructure damage such as utility outages, and the experience of personal trauma through the loss of loved ones, homes, or economic livelihoods; all of which are intensified when storms hit densely populated urban centers. Government agencies and policymakers have called for enhancing citizens? resilience as a way to prepare populations in advance of disasters with an emphasis on promoting community resilience through scholarly, policy, and programmatic efforts. Large and high-profile funding initiatives from the federal government and nonprofit organizations underscore the importance of incorporating community resilience into a policy framework. These efforts have necessitated a business case for community resilience, leading to the development of a large and growing set of metrics and indicators to measure it. Despite the promise of community resilience for improving population health outcomes post- disaster, validation of readily-available community resilience metrics against a broad range of physical health outcomes is lacking. Empirical evidence is needed to determine if communities with higher pre-disaster resilience sustain fewer adverse health impacts from a disaster or storm than communities with lower pre- disaster resilience, and if so, to determine which domains of resilience are most important for health. Without such evidence, government efforts to promote community resilience will be unfocused and ineffective at providing direction to communities and the potential benefits for population health may never be fully realized. In the proposed work, we will examine these issues within the context of Hurricane Sandy by combining multiple data sources of health outcomes from New York and New Jersey, storm severity, and community resilience metrics to create an aggregated analytic data file. Using a hierarchical time-series methodological approach we will analyze the aggregated data file to (1) estimate the increase in risk (overall and by county) in emergency department (ED) visits and hospitalization admissions for respiratory, cardiovascular, renal, and mental health causes due to Sandy; (2) determine the amount of risk variation across counties in Hurricane Sandy-related (respiratory, cardiovascular, renal, and mental health) ED visits and hospitalization admissions that can be explained by county-level community resilience metrics, after adjusting for storm severity; and (3) calculate the number and costs of [1] ED visits and hospitalizations associated with Hurricane Sandy, and [2] avoidable ED visits and hospitalizations associated with community resilience metrics.